code: def get_backend(self, model: BackendModel) -> TensorDockBackend:
      config = self._get_backend_config(model)
      return TensorDockBackend(config=config)
  
file_path: dstack/src/dstack/_internal/server/services/backends/configurators/tensordock.py
imports: import json
  from typing import List
  from dstack._internal.core.backends.tensordock import TensorDockBackend, api_client
  from dstack._internal.core.backends.tensordock.config import TensorDockConfig
  from dstack._internal.core.models.backends.base import BackendType, ConfigElementValue, ConfigMultiElement
  from dstack._internal.core.models.backends.tensordock import AnyTensorDockConfigInfo, TensorDockConfigInfo, TensorDockConfigInfoWithCreds, TensorDockConfigInfoWithCredsPartial, TensorDockConfigValues, TensorDockCreds, TensorDockStoredConfig
  from dstack._internal.server.models import BackendModel, ProjectModel
  from dstack._internal.server.services.backends.configurators.base import Configurator, raise_invalid_credentials_error
label_desc: Use image node_id 5 for calling the TensorDockConfigurator obj's underlying member method code with example usage: obj.get_backend(model) and returns: TensorDockBackend